update the dates on the schedule page, remove dates from course slides

_footer.html

@@ -2,5 +2,5 @@
 <p> Cengiz Zopluoglu, [email protected] </p>
 <p> Made using <a href="https://rstudio.github.io/distill/website.html"> the Distill for R Markdown</a> in 
 <a href = "https://www.rstudio.com"> RStudio.</a></p>
-<p>Copyright &copy; 2022 Cengiz Zopluoglu. All rights reserved.</p>
+<p>Copyright &copy; 2023-2024 Cengiz Zopluoglu. All rights reserved.</p>
 </center>

_site/data/schedule.csv

@@ -1,8 +1,8 @@
 date,notes,notes_link,kaggle,kaggle_link,slides,slides_link,reading,reading_link,assignments,assignments_link
-3-Oct,Lecture-1,https://edld654-fall23.netlify.app/lecture-1.html,Notebook-1,https://www.kaggle.com/code/uocoeeds/week-1-introduction/notebook,Week 1,https://edld654-fall23.netlify.app/slides/slide1.html,Kaggle CommonLit Readability Competition;NIJ Recidivism Challenge,https://www.kaggle.com/c/commonlitreadabilityprize/;https://nij.ojp.gov/funding/recidivism-forecasting-challenge,,
-10-Oct,Lecture-2a;Lecture-2b,https://edld654-fall23.netlify.app/lecture-2a.html;https://edld654-fall23.netlify.app/lecture-2b.html,Notebook-2a;Notebook-2b;  The {recipes} demo,https://www.kaggle.com/code/uocoeeds/lecture-2a-data-preprocessing-i;https://www.kaggle.com/code/uocoeeds/lecture-2b-data-preprocessing-ii;https://www.kaggle.com/code/uocoeeds/the-recipes-package-demo,Week 2,https://edld654-fall23.netlify.app/slides/slide2.html,"Kuhn & Johnson, Ch. 6;Kuhn & Johnson, Ch. 5;Boehmke & Greenwell, Ch. 3",http://www.feat.engineering/engineering-numeric-predictors.html;http://www.feat.engineering/encoding-categorical-predictors.html;https://bradleyboehmke.github.io/HOML/engineering.html,Assignment 1,https://www.kaggle.com/code/uocoeeds/assignment-1/
-17-Oct & 24-Oct,Lecture-3a;Lecture-3b,https://edld654-fall23.netlify.app/lecture-3a.html;https://edld654-fall23.netlify.app/lecture-3b.html,Notebook-3a; Notebook-3b; Building a Linear Model with `caret`,https://www.kaggle.com/code/uocoeeds/lecture-3a-overview-of-linear-regression;https://www.kaggle.com/code/uocoeeds/lecture-3b-review-of-bias-variance-tradeoff;https://www.kaggle.com/code/uocoeeds/building-a-prediction-model-with-cross-validation,Week 3 & 4,https://edld654-fall23.netlify.app/slides/slide3.html," Boehmke & Greenwell, Ch. 2;Boehmke & Greenwell, Ch. 4; James et al. Ch.3; Kuhn and Johnson, APM, Ch. 4, 5.1, and Ch.6",https://bradleyboehmke.github.io/HOML/process.html;https://bradleyboehmke.github.io/HOML/linear-regression.html;https://hastie.su.domains/ISLR2/ISLRv2_website.pdf;https://edld654-fall23.netlify.app/schedule.html,,
-31-Oct,Lecture-4,https://edld654-fall23.netlify.app/lecture-4.html,Notebook-4;  Building a Ridge Regression Model;Building a Lasso Regression Model; Building an Elastic Net Model; Using the Prediction Models for a New Text,https://www.kaggle.com/code/uocoeeds/lecture-4-regularized-penalized-regression;https://www.kaggle.com/code/uocoeeds/building-a-ridge-regression-model;https://www.kaggle.com/code/uocoeeds/building-a-lasso-regression-model;https://www.kaggle.com/code/uocoeeds/building-a-regression-model-with-elastic-net;https://www.kaggle.com/code/uocoeeds/using-the-prediction-models-for-a-new-text,Week 5,https://edld654-fall23.netlify.app/slides/slide4.html," Boehmke & Greenwell, Ch. 6; James et al., Ch.6.2",https://bradleyboehmke.github.io/HOML/regularized-regression.html; https://edld654-fall23.netlify.app/schedule.html,,
-7-Nov & 14-Nov,Lecture-5,https://edld654-fall23.netlify.app/lecture-5.html,Building a Logistic Regression Model;Building a Classification Model with Ridge Penalty;Building a Classification Model with Lasso Penalty;Building a Classification Model with Elastic Net,https://www.kaggle.com/code/uocoeeds/building-a-logistic-regression-model/notebook;https://www.kaggle.com/code/uocoeeds/building-a-classification-model-with-ridge-penalty/;https://www.kaggle.com/code/uocoeeds/building-a-classification-model-with-lasso-penalty;https://www.kaggle.com/code/uocoeeds/building-a-classification-model-with-elastic-net,Week 6 & 7,https://edld654-fall23.netlify.app/slides/slide5.html,"Boehmke & Greenwell, Ch. 5;  James et al., Ch. 4.3; APM, Ch. 12.2 and 12.5",https://bradleyboehmke.github.io/HOML/logistic-regression.html;https://edld654-fall23.netlify.app/schedule.html;https://edld654-fall23.netlify.app/schedule.html,Assignment 2,https://www.kaggle.com/code/uocoeeds/assignment-2
-21-Nov,Lecture-6a;Lecture-6b,https://edld654-fall23.netlify.app/lecture-6a.html;https://edld654-fall23.netlify.app/lecture-6b.html,Building a Prediction Model with K-nearest neighbors;Building a Classification Model with K-nearest neighbors;Building a Prediction Model with a Decision Tree;Building a Classification Model with a Decision Tree,https://www.kaggle.com/code/uocoeeds/building-a-prediction-model-using-knn;https://www.kaggle.com/code/uocoeeds/building-a-classification-model-using-knn;https://www.kaggle.com/uocoeeds/building-a-prediction-model-using-a-decision-tree;https://www.kaggle.com/code/uocoeeds/building-a-classification-tree-algorithm,Week 8_Part 1;Week 8_Part 2,https://edld654-fall23.netlify.app/slides/slide6a.html;https://edld654-fall23.netlify.app/slides/slide6b.html,"Boehmke & Greenwell, Ch. 8; Boehmke & Greenwell, Ch. 9; APM Ch. 13.5; James et al. Ch. 8.1",https://bradleyboehmke.github.io/HOML/knn.html;https://bradleyboehmke.github.io/HOML/DT.html;https://edld654-fall23.netlify.app/schedule.html;https://edld654-fall23.netlify.app/schedule.html,,
-28-Nov,Lecture-7a;Lecture-7b,https://edld654-fall23.netlify.app/lecture-7a.html;https://edld654-fall23.netlify.app/lecture-7b.html,,,,,"Boehmke & Greenwell, Ch. 10; Boehmke & Greenwell, Ch. 11; Boehmke & Greenwell, Ch. 12; APM Ch. 8 & 14; James et al. Ch. 8.2",https://bradleyboehmke.github.io/HOML/bagging.html;https://bradleyboehmke.github.io/HOML/random-forest.html;https://bradleyboehmke.github.io/HOML/gbm.html; https://edld654-fall23.netlify.app/schedule.html; https://edld654-fall23.netlify.app/schedule.html,Assignment 3,https://www.kaggle.com/code/uocoeeds/assignment-3
+2-Oct,Lecture-1,https://edld654-fall23.netlify.app/lecture-1.html,Notebook-1,https://www.kaggle.com/code/uocoeeds/week-1-introduction/notebook,Week 1,https://edld654-fall23.netlify.app/slides/slide1.html,Kaggle CommonLit Readability Competition;NIJ Recidivism Challenge,https://www.kaggle.com/c/commonlitreadabilityprize/;https://nij.ojp.gov/funding/recidivism-forecasting-challenge,,
+9-Oct,Lecture-2a;Lecture-2b,https://edld654-fall23.netlify.app/lecture-2a.html;https://edld654-fall23.netlify.app/lecture-2b.html,Notebook-2a;Notebook-2b;  The {recipes} demo,https://www.kaggle.com/code/uocoeeds/lecture-2a-data-preprocessing-i;https://www.kaggle.com/code/uocoeeds/lecture-2b-data-preprocessing-ii;https://www.kaggle.com/code/uocoeeds/the-recipes-package-demo,Week 2,https://edld654-fall23.netlify.app/slides/slide2.html,"Kuhn & Johnson, Ch. 6;Kuhn & Johnson, Ch. 5;Boehmke & Greenwell, Ch. 3",http://www.feat.engineering/engineering-numeric-predictors.html;http://www.feat.engineering/encoding-categorical-predictors.html;https://bradleyboehmke.github.io/HOML/engineering.html,Assignment 1,https://www.kaggle.com/code/uocoeeds/assignment-1/
+16-Oct & 23-Oct,Lecture-3a;Lecture-3b,https://edld654-fall23.netlify.app/lecture-3a.html;https://edld654-fall23.netlify.app/lecture-3b.html,Notebook-3a; Notebook-3b; Building a Linear Model with `caret`,https://www.kaggle.com/code/uocoeeds/lecture-3a-overview-of-linear-regression;https://www.kaggle.com/code/uocoeeds/lecture-3b-review-of-bias-variance-tradeoff;https://www.kaggle.com/code/uocoeeds/building-a-prediction-model-with-cross-validation,Week 3 & 4,https://edld654-fall23.netlify.app/slides/slide3.html," Boehmke & Greenwell, Ch. 2;Boehmke & Greenwell, Ch. 4; James et al. Ch.3; Kuhn and Johnson, APM, Ch. 4, 5.1, and Ch.6",https://bradleyboehmke.github.io/HOML/process.html;https://bradleyboehmke.github.io/HOML/linear-regression.html;https://hastie.su.domains/ISLR2/ISLRv2_website.pdf;https://edld654-fall23.netlify.app/schedule.html,,
+30-Oct,Lecture-4,https://edld654-fall23.netlify.app/lecture-4.html,Notebook-4;  Building a Ridge Regression Model;Building a Lasso Regression Model; Building an Elastic Net Model; Using the Prediction Models for a New Text,https://www.kaggle.com/code/uocoeeds/lecture-4-regularized-penalized-regression;https://www.kaggle.com/code/uocoeeds/building-a-ridge-regression-model;https://www.kaggle.com/code/uocoeeds/building-a-lasso-regression-model;https://www.kaggle.com/code/uocoeeds/building-a-regression-model-with-elastic-net;https://www.kaggle.com/code/uocoeeds/using-the-prediction-models-for-a-new-text,Week 5,https://edld654-fall23.netlify.app/slides/slide4.html," Boehmke & Greenwell, Ch. 6; James et al., Ch.6.2",https://bradleyboehmke.github.io/HOML/regularized-regression.html; https://edld654-fall23.netlify.app/schedule.html,,
+6-Nov & 13-Nov,Lecture-5,https://edld654-fall23.netlify.app/lecture-5.html,Building a Logistic Regression Model;Building a Classification Model with Ridge Penalty;Building a Classification Model with Lasso Penalty;Building a Classification Model with Elastic Net,https://www.kaggle.com/code/uocoeeds/building-a-logistic-regression-model/notebook;https://www.kaggle.com/code/uocoeeds/building-a-classification-model-with-ridge-penalty/;https://www.kaggle.com/code/uocoeeds/building-a-classification-model-with-lasso-penalty;https://www.kaggle.com/code/uocoeeds/building-a-classification-model-with-elastic-net,Week 6 & 7,https://edld654-fall23.netlify.app/slides/slide5.html,"Boehmke & Greenwell, Ch. 5;  James et al., Ch. 4.3; APM, Ch. 12.2 and 12.5",https://bradleyboehmke.github.io/HOML/logistic-regression.html;https://edld654-fall23.netlify.app/schedule.html;https://edld654-fall23.netlify.app/schedule.html,Assignment 2,https://www.kaggle.com/code/uocoeeds/assignment-2
+20-Nov,Lecture-6a;Lecture-6b,https://edld654-fall23.netlify.app/lecture-6a.html;https://edld654-fall23.netlify.app/lecture-6b.html,Building a Prediction Model with K-nearest neighbors;Building a Classification Model with K-nearest neighbors;Building a Prediction Model with a Decision Tree;Building a Classification Model with a Decision Tree,https://www.kaggle.com/code/uocoeeds/building-a-prediction-model-using-knn;https://www.kaggle.com/code/uocoeeds/building-a-classification-model-using-knn;https://www.kaggle.com/uocoeeds/building-a-prediction-model-using-a-decision-tree;https://www.kaggle.com/code/uocoeeds/building-a-classification-tree-algorithm,Week 8_Part 1;Week 8_Part 2,https://edld654-fall23.netlify.app/slides/slide6a.html;https://edld654-fall23.netlify.app/slides/slide6b.html,"Boehmke & Greenwell, Ch. 8; Boehmke & Greenwell, Ch. 9; APM Ch. 13.5; James et al. Ch. 8.1",https://bradleyboehmke.github.io/HOML/knn.html;https://bradleyboehmke.github.io/HOML/DT.html;https://edld654-fall23.netlify.app/schedule.html;https://edld654-fall23.netlify.app/schedule.html,,
+27-Nov,Lecture-7a;Lecture-7b,https://edld654-fall23.netlify.app/lecture-7a.html;https://edld654-fall23.netlify.app/lecture-7b.html,,,,,"Boehmke & Greenwell, Ch. 10; Boehmke & Greenwell, Ch. 11; Boehmke & Greenwell, Ch. 12; APM Ch. 8 & 14; James et al. Ch. 8.2",https://bradleyboehmke.github.io/HOML/bagging.html;https://bradleyboehmke.github.io/HOML/random-forest.html;https://bradleyboehmke.github.io/HOML/gbm.html; https://edld654-fall23.netlify.app/schedule.html; https://edld654-fall23.netlify.app/schedule.html,Assignment 3,https://www.kaggle.com/code/uocoeeds/assignment-3

_site/schedule.html

@@ -2257,7 +2257,7 @@ <h3 id="week-1-introduction">Week 1: Introduction</h3>
 <tbody>
 <tr>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
-3-Oct
+2-Oct
 </td>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
 <a href="https://edld654-fall23.netlify.app/lecture-1.html" style="     ">Lecture-1</a>
@@ -2306,7 +2306,7 @@ <h3 id="week-2-data-preprocessing">Week 2: Data Preprocessing</h3>
 <tbody>
 <tr>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
-10-Oct
+9-Oct
 </td>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
 <a href="https://edld654-fall23.netlify.app/lecture-2a.html" style="     ">Lecture-2a</a><br><a href="https://edld654-fall23.netlify.app/lecture-2b.html" style="     ">Lecture-2b</a>
@@ -2355,7 +2355,7 @@ <h3 id="week-3-week-4-introduction-to-linear-regression-biasvariance-tradeoff-an
 <tbody>
 <tr>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
-17-Oct &amp; 24-Oct
+16-Oct &amp; 23-Oct
 </td>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
 <a href="https://edld654-fall23.netlify.app/lecture-3a.html" style="     ">Lecture-3a</a><br><a href="https://edld654-fall23.netlify.app/lecture-3b.html" style="     ">Lecture-3b</a>
@@ -2404,7 +2404,7 @@ <h3 id="week-5-regularized-linear-regression">Week 5: Regularized Linear Regress
 <tbody>
 <tr>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
-31-Oct
+30-Oct
 </td>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
 <a href="https://edld654-fall23.netlify.app/lecture-4.html" style="     ">Lecture-4</a>
@@ -2453,7 +2453,7 @@ <h3 id="week-6-7-regularized-logistic-regression">Week 6 &amp; 7: (Regularized)
 <tbody>
 <tr>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
-7-Nov &amp; 14-Nov
+6-Nov &amp; 13-Nov
 </td>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
 <a href="https://edld654-fall23.netlify.app/lecture-5.html" style="     ">Lecture-5</a>
@@ -2502,7 +2502,7 @@ <h3 id="week-8-introduction-to-k-nearest-neighbors-and-decision-tree-algorithms"
 <tbody>
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 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
-21-Nov
+20-Nov
 </td>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
 <a href="https://edld654-fall23.netlify.app/lecture-6a.html" style="     ">Lecture-6a</a><br><a href="https://edld654-fall23.netlify.app/lecture-6b.html" style="     ">Lecture-6b</a>
@@ -2551,7 +2551,7 @@ <h3 id="week-9-introduction-to-bagged-trees-random-forests-and-gradient-boosting
 <tbody>
 <tr>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
-28-Nov
+27-Nov
 </td>
 <td style="text-align:left;border-bottom: solid;border-top: solid;border-left: solid;border-right: solid;">
 <a href="https://edld654-fall23.netlify.app/lecture-7a.html" style="     ">Lecture-7a</a><br><a href="https://edld654-fall23.netlify.app/lecture-7b.html" style="     ">Lecture-7b</a>